Methods, systems, and apparatus for identification and characterization of rotors associated with atrial fibrillation

ABSTRACT

A system can include a near-field instrument to be placed inside a chamber of a heart, a far-field instrument to be placed in a stable position in relation to the heart, and a control unit. The control unit is configured to identify a unique pattern in electrogram information received from the far-field instrument when the near-field instrument is in one or more positions within the heart. When the unique pattern is detected, the control unit is configured to receive electrogram information from the near-field instrument. While recording electrogram information from the near-field instrument, the control unit is also configured to record voltage and complex fractionated atrial electrogram (CFAE) characteristics of the tissue inside a heart chamber. This information combined with rotor information can be used to identify substrate versus non-substrate rotor characteristics.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.15/355,909, filed Nov. 18, 2016, now U.S. Pat. No. 9,955,893, which is acontinuation of U.S. patent application Ser. No. 14/737,116, filed Jun.11, 2015, now U.S. Pat. No. 9,498,143, which is a continuation of U.S.patent application Ser. No. 14/466,588, filed Aug. 22, 2014, now U.S.Pat. No. 9,078,583, each of which is incorporated herein by reference inits entirety. U.S. patent application Ser. No. 14/466,588, now U.S. Pat.No. 9,078,583, claims priority to and the benefit of U.S. ProvisionalPatent Application No. 61/868,950, filed Aug. 22, 2013 and U.S.Provisional Patent Application No. 61/988,651, filed May 5, 2014, eachof which is incorporated herein by reference in its entirety.

BACKGROUND

The invention relates generally to methods, systems, and apparatus foridentifying and characterizing rotors associated with heart arrhythmiassuch as atrial fibrillation. Some methods described herein are suitablefor classifying rotors as substrate rotors, which may significantlyinfluence arrhythmias, and non-substrate rotors, which may not stronglyinfluence arrhythmias.

In the last few years, scientific understanding of atrial fibrillationhas discovered that the electrical activity in the heart during atrialfibrillation is not complete chaos as was once accepted under the Moemodel of random wavelets of electrical activity causing atrialfibrillation. Rather, there are local organized electrical drivers ofatrial fibrillation. Recent research has revealed that electricalpatterns in the heart, commonly referred to as rotors, play an importantrole in many cases of fibrillation, particularly persistent atrialfibrillation. Currently, surgical systems are available that modifycardiac tissue during treatment using RF energy, cryo, laser, directcurrent (DC), stem-cells, or drugs. In some situations modifying,ablating, or “burning” a rotor can significantly improve cardiacfunction by returning the patient to normal sinus heartbeat rhythm.

Known surgical techniques, however, have inconsistent results; ablationof some rotors results in significant changes in heart rhythm, whileablation of other rotors does not have a significant effect. Currentmedical equipment and techniques cannot identify which rotors will havea significant effect if ablated. A need therefore exists for methods,systems, and apparatus for identifying and characterizing rotors.Furthermore, a targeted approach to treating rotors in atrialfibrillation patients will shorten treatment procedure times, reducecost of procedures, reduce the need for repeat procedures, preserveheart tissue, and enable patients to live longer and fuller lives.

SUMMARY OF THE INVENTION

In some embodiments, a system includes a near-field instrument to beplaced inside a chamber of a heart, a far-field instrument to be placedin a stable position in relation to the heart (e.g., the coronarysinus), and a control unit. The control unit is configured to receiveposition coordinates of the near-field instrument and electrograminformation from the far-field instrument. The control unit isconfigured to identify a unique pattern in the electrogram informationfrom the far-field instrument. When the unique pattern is detected, thecontrol unit is configured to receive electrogram information from thenear-field instrument and store the associated near-field instrumentposition information with the unique pattern information and near-fieldinstrument electrogram information. Upon moving the near-fieldinstrument within the heart chamber, the control unit is configured toidentify the unique pattern in the electrogram information from thefar-field instrument again. Upon detecting the unique pattern, thecontrol unit is configured to receive electrogram information from thenear-field instrument at the new position and store the associated newnear-field instrument position information with the unique patterninformation and near-field instrument electrogram information. Whilerecording electrogram information from the near-field instrument, thecontrol unit is also configured to receive voltage and complexfractionated atrial electrogram (CFAE) characteristics of the tissuefrom the near-field instrument. This information combined with rotorinformation can be used to determine substrate versus non-substraterotor characteristics.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a flow chart of a method of treating a cardiac arrhythmia,according to an embodiment.

FIGS. 2A and 2B depict electro-anatomical models of a left atriumshowing cardiac electrical conduction patterns in two unique phases,according to an embodiment.

FIG. 2C depicts an electro-anatomical model of the left atrium of FIGS.2A and 2B showing a map of the voltage characteristics of the underlyingtissue, according to an embodiment.

FIG. 2D depicts an electro-anatomical model of the left atrium of FIGS.2A-2C showing a map of the complex fractionation characteristics of theunderlying tissue, according to an embodiment.

FIG. 3A depicts an electro-anatomical model of a left atrium showingconduction patterns and sites where tissue was burned or ablated in thepatient, according to an embodiment.

FIG. 3B depicts an electro-anatomical model of the left atrium of FIG.3A showing a voltage map, according to an embodiment.

FIG. 4 is a flow chart of a method for classifying rotors, according toan embodiment.

FIG. 5A illustrates a human heart having a multi-electrode catheterinstrument located in the coronary sinus, according to an embodiment.

FIG. 5B illustrates a human heart having a multi-electrode catheterinstrument with electrodes located in the left atrium, according to anembodiment.

FIG. 5C illustrates a pattern template of electrogram data, according toan embodiment.

FIG. 5D illustrates measured conduction vectors in a left atrium,according to an embodiment.

FIG. 6A illustrates a cardiac electrogram signal, according to anembodiment.

FIG. 6B illustrates the identification of a timing of when heart cellsare contracting along a cardiac electrical conduction path, according toan embodiment.

FIG. 6C illustrates multiple signals at different electrodes on amulti-electrode catheter instrument being used to calculate conductionvectors, according to an embodiment.

FIG. 7 illustrates a look-up table storing conduction vectors associatedwith different positions in a heart and times when different patternsare occurring on a stable instrument, according to an embodiment.

FIGS. 8A-8C are depictions of conduction vectors and the calculationsthat allow interpolation of conduction vectors throughout a region ofthe heart based on actual measured conduction vectors, according to anembodiment.

FIG. 9A illustrates the identification and ablation of a substrate basedrotor in the left atrium, according to an embodiment.

FIG. 9B illustrates a voltage map of the left atrium where a substratebased rotor was identified, according to an embodiment.

FIG. 9C depicts the electrical activity of a heart in fibrillation priorto an ablation at a substrate rotor site and the electrical activity ofthe heart in normal sinus rhythm just after the ablation at thesubstrate rotor site, according to an embodiment.

FIG. 10 illustrates an instrument having electrodes, according to anembodiment.

FIG. 11 is a flow chart of a method of constructing a conduction vectormap, according to an embodiment.

DETAILED DESCRIPTION

In some embodiments, a system includes a near-field instrument to beplaced inside a chamber of a heart, a far-field instrument to be placedin a stable position in relation to the heart (e.g., the coronarysinus), and a control unit. The control unit is configured to receiveposition coordinates of the near-field instrument and electrograminformation from the far-field instrument. The control unit isconfigured to identify a unique pattern in the electrogram informationfrom the far-field instrument. When the unique pattern is detected, thecontrol unit is configured to receive electrogram information from thenear-field instrument and store the associated near-field instrumentposition information with the unique pattern information and near-fieldinstrument electrogram information. Upon moving the near-fieldinstrument within the heart chamber, the control unit is configured toidentify the unique pattern in the electrogram information from thefar-field instrument again. Upon detecting the unique pattern, thecontrol unit is configured to receive electrogram information from thenear-field instrument at the new position and store the associated newnear-field instrument position information with the unique patterninformation and the near-field instrument electrogram informationassociated with the new position.

In some embodiments, a method includes receiving position coordinates ofa near-field instrument from within a patient's heart chamber andelectrogram information from a far-field instrument that is located at astable position with respect to the patient's heart. The method furtherincludes identifying a pattern in the far-field electrogram data,capturing electrogram data from the near-field instrument when thepattern is detected in the far-field electrogram data, and associatingin memory the position coordinates and electrogram data of thenear-field instrument and the identified pattern. The method furtherincludes moving the position of the near-field instrument within thepatient's heart chamber and repeating the steps to gather near-fieldelectrogram data at the new position when the pattern is identified inthe electrogram data of the far-field instrument.

In some embodiments, a method including identifying the location of oneor more rotors (i.e., spiraling conduction vector patterns) in apatient's heart. Once the locations are identified, determining thestability of each of the rotors, measuring voltage characteristics andcomplex fractionation characteristics of the heart tissue in and aroundthe rotor location, and using the stability information andcharacteristic information to identify which rotors are sources ofarrhythmia.

As used herein, the singular forms “a,” “an,” and “the” include pluralreferents unless the context clearly dictates otherwise. Thus, forexample, the term “an electrode” is intended to mean a single electrodeor a combination of electrodes.

FIG. 1 illustrates a flow chart of a method 100 of treating a cardiacarrhythmia. At 110, a control unit can receive cardiac imaging data. Thecardiac imaging data, also commonly referred to as an electro-anatomicalmap, a three-dimensional (3D) heart geometry, or a geometry, can be datacreated from a cluster of 3D points created by tracking an instrumentinside the heart as it is used to paint the interior surface of achamber or from applying edge detection algorithms to computerizedtomography (CT) scan, magnetic resonance imaging (MRI), ultrasound,x-ray, and/or any other suitable imaging technology to identify heartwall surfaces. In some embodiments, the imaging data can be suitable togenerate, define, and/or render a 3D model of the heart, for example,using various linear and non-linear 3D registration techniques. In someembodiments, the imaging data can include time data such that afour-dimensional (4D) model of the heart can be generated, defined,and/or rendered. For example, a video, real-time, and/or animated modelof the heart can be created using the cardiac imaging data.

At 120, a control unit can receive near- and/or far-field cardiacelectrogram (EGM) data. For example, a near-field measurement instrumentcan be used to measure a patient's heart signal. The near-fieldmeasurement instrument can be an instrument having one or moreelectrodes, such as the instrument depicted in FIG. 10 and described inmore detail herein. For example, the near-field instrument can be a loopcatheter with electrodes, a basket catheter with electrodes that isdesigned to fill a heart chamber, a basket catheter with electrodes thatis designed to partially fill a heart chamber, a star shaped catheterwith electrodes, or any another suitable multi-electrode cathetercapable of sensing cardiac electrical activity. In some embodiments, thenear-field measurement instrument can be the antenna catheter instrumentdescribed with respect to FIG. 10.

In some embodiments, the near-field measurement instrument can have anelectromagnetic sensor integrated into it such that the near-fieldmeasurement instrument can be localized by a tracking system. In someembodiments, the near-field measurement instrument can be localized bytracking systems that utilize electromagnetic, electropotential,impedance, or any other suitable technology for tracking. For example,the tracking system can be the tracking system disclosed in U.S. patentapplication Ser. No. 13/747,266 to Edwards, filed on Jan. 22, 2013, nowU.S. Pat. No. 9,510,772, entitled “System and Methods for LocalizingMedical Instruments During Cardiovascular Medical Procedures,” which isincorporated by reference herein in its entirety.

In some embodiments, the near-field measurement instrument can be placedwithin a chamber of a patient's heart for measuring the patient's heartsignal and capturing electromagnetic positional information. Theinstrument can be moved within the chamber of the patient's heart tocapture positional and electrogram data at multiple locations within thechamber of the patient's heart as described in more detail herein withrespect to FIG. 11.

In some embodiments, a far-field measurement instrument can be used tomeasure a patient's heart signal from a distance. The far-fieldmeasurement instrument can be, for example, a coronary sinus cathetercapable of sensing cardiac electrogram activity, such as the instrumentdepicted in FIG. 10 and described in more detail herein. For anotherexample, a far-field measurement instrument can be multiple electrodesplaced on the body surface of the patient with the capability of sensingcardiac electrical activity from a distance. In some embodiments, thefar-field measurement instrument can have an electromagnetic sensorintegrated into it such that the far-field measurement instrument can belocalized by a positional tracking system. For example, the far-fieldmeasurement instrument can be localized by tracking systems that utilizeelectromagnetic, electropotential, impedance, or any other suitabletechnology for tracking the location of the instrument with respect tothe patient's heart. The tracking system can be, for example, thetracking system disclosed in U.S. patent application Ser. No. 13/747,266as described above.

In some embodiments, the far-field instrument can be placed in relationto the patent's heart such that it is in a stable location. For example,a coronary sinus catheter can be placed within the coronary sinus of thepatent's heart, which is a stable location with respect to the patient'sheart. In other words, the far-field instrument can be an instrumentthat does not move with respect to the patient's heart during the courseof the patient's cardiac arrhythmia treatment. In some embodiments, thefar-field instrument can be placed more specifically in a stablelocation with respect to the patient's left atrium where sources ofatrial fibrillation tend to be found.

The near-field measurement instrument can capture data at variouslocations and positional data in X-Y-Z space, which can be sent to andreceived by a control unit for processing as described in further detailherein with respect to FIG. 11. The near-field measurement data can bestored in a computer memory, including RAM, ROM, flash drive, externalhard drive, or any other suitable memory device. The data can beconfigured to be stored in a database, lookup table, and/or any othersuitable configuration for storing data, such as, for example, asdescribed in further detail herein with respect to FIG. 7. Furthermore,the far-field measurement instrument can capture data associated witheach near-field measured point. The far-field data can be stored in acomputer memory, including RAM, ROM, flash drive, external hard drive,or any other suitable memory device. The data can be configured to bestored in a database, lookup table, and/or any other suitableconfiguration for storing data. The capture and storage of data from thefar-field instrument and the near-field instrument will be described infurther detail herein with respect to FIGS. 5 and 11.

At 130, the electrogram data received at 120 and the imaging datareceived at 110 can be combined or integrated to define anelectro-anatomical model, such as the model of FIG. 2A or FIG. 2B.Specifically, FIG. 2A represents one phase of atrial fibrillationcorresponding to one pattern detected on the far-field instrument andFIG. 2B represents a second phase of atrial fibrillation correspondingto a second pattern detected on the far-field instrument. Theelectro-anatomical model can be a 3D or 4-dimensional (4D) model of aheart, or a portion thereof, including a visualization (e.g., a vectorfield, heat map, and/or any other suitable visualization) of electricpotentials, conduction patterns, velocities, and/or any other suitableelectro-anatomic feature, such as, for example, CFAE mapping.

The electro-anatomical models can be constructed using a control unitthat can be configured to find patterns on the far-field data and indexnear-field cardiac electrical data and near-field instrument positionlocation information to far-field data patterns. The control unit canorganize a set of near-field cardiac electrical data from multiplenear-field position locations that display the same far-field datapatterns as described in more detail with respect to FIGS. 5 and 11. Thecontrol unit can use this set of data and various interpolationtechniques to generate a 3D map of electrical activity for a region ofthe heart corresponding to that far-field data pattern. This process canbe repeated for multiple far-field data patterns to create multiplemaps. These multiple maps can correspond to different repeating phasesof atrial fibrillation as detected by the patterns in the far-fielddata. As described in more detail herein, these multiple maps can besequenced to create a composite 4D map of an arrhythmia such as atrialfibrillation over time.

As an example of the 3D mapping, FIGS. 2A and 2B depict 3D left atrialelectro-anatomical models of a human heart. Electro-anatomical models200 and 225 depict the left atrium of the heart during two separatephases of atrial fibrillation. Further, electro-anatomical models 200and 225 each show cardiac conduction patterns during its respectivephase. As seen in electro-anatomical models 200 and 225, the conductionpatterns can be used to identify contraction of heart muscle.Contraction of heart muscle can sometimes be seen within theelectro-anatomical model as conduction patterns that appear to swirl orform a circular pattern. The swirling conduction patterns can be used toidentify rotors within the heart tissue.

At 140, the electro-anatomical model can be used to identify rotors.Rotors can be identified by any suitable technique. For example, withrespect to FIG. 2A, within electro-anatomical model 200, two locationsof swirling conduction vectors 210, 220 can be identified. The thick,white arrows that form a circular or swirling pattern 210 can be used toidentify the substrate based rotor 205. The thick, black arrows thatform a circular or swirling pattern 220 can be used to identify thenon-substrate based rotor 215. Note that, as described in more detailherein with respect to FIG. 4, the substrate based rotor 205 is presentin multiple phases of conduction as depicted in FIG. 2A and FIG. 2B andis thereby more stable than the non-substrate based rotor 215 that isonly present in one phase of conduction as depicted in FIGS. 2A and 2B.With only a single electro-anatomical model, the rotor locations 205 and215 can be identified, but the rotors cannot be classified as substratebased or non-substrate based without more information.

Stated differently, rotors can be identified, in some embodiments, usinga computational mapping algorithm to, for example, integratespatiotemporal wave front patterns during atrial fibrillation on theelectro-anatomical model defined at 130. For example, the computationalmapping algorithm can search the surface of the electro-anatomical modeldefined at 130 for complete rotation of conduction velocity vectors. Insome embodiments, the complete surface of the model can be searched andone or more rotors can be identified. In some embodiments, when a rotoris identified, the region of rotation associated with the rotor can besearched for additional rotations (e.g., partial and/or completerotations), for example, over multiple phases. In some embodiments, inaddition to or instead of identifying regions of rotation from theelectro-anatomical model, voltage transition zones in the underlyingtissue can be located and identified by the near-field instrument duringdata capture, for example, within a region of rotation. In someembodiments, multiple rotors can be associated with a voltage transitionzone within a region of rotation. In fact, these tissue voltagetransition zones can act like high pressure and low pressure borderingweather patterns that create tornados in nature. In some embodiments,information such as rotor phase percentage, change in voltage betweenthe rotor and an adjacent region, and/or degree of complex fractionationfor the region containing the rotor can be calculated and/or determinedfor each rotor. All of this data can be gathered by the control unitduring near-field instrument data sampling at various positions withinthe heart.

At 150, further information can be used to classify the rotors assubstrate based or non-substrate based. An example of a process forusing the information to classify rotors will be described in moredetail herein with respect to FIG. 4. In some embodiments, the swirlingconduction patterns in addition to other information including thestability of the swirling conduction patterns, the voltage of the hearttissue near the swirling conduction patterns, and the complexfractionation of the heart tissue near the swirling conduction patternscan be used to identify which locations within the heart can be causingarrhythmia. Where the information indicates a cause of arrhythmia, theswirling conduction patterns can be used to identify a substrate basedrotor location. Where the information indicates that the location is nota true cause of arrhythmia, the swirling conduction patterns can be usedto identify a non-substrate based rotor location. Stated differently,rotors that are classified as substrate rotors can be associated withcausing and/or driving arrhythmias, while rotors that are classified asnon-substrate rotors may not be associated with a true arrhythmia causeand may simply be the result of electrical wavefront collisions.

As will be described in further detail herein, the substrate based rotor205, partially characterized by the swirling conduction pattern 210, isindicated in the phase depicted in electro-anatomical model 200 as wellas in the phase depicted in electro-anatomical model 250. Thenon-substrate based rotor 215 is shown in electro-anatomical model 200characterized by the swirling conduction pattern 220. The swirlingconduction pattern 220 does not appear in electro-anatomical model 225,indicating that the rotor 215 is a non-substrate based rotor because itis unstable. Where a rotor is stable, the swirling conduction patternwill appear in electro-anatomical models of multiple phases. Phases willbe described in more detail herein with respect to FIG. 11.

FIG. 2C depicts the left atrium of FIGS. 2A and 2B showing a voltage map250 of the left atrium. The voltage map 250 highlights areas of healthytissue (i.e., high voltage) versus scar or unhealthy tissue (i.e., lowvoltage). While difficult to see in the grey-scale depiction of FIG. 2C,the area around non-substrate based rotor 215 is homogeneous in voltage.Contrastingly, the area around substrate based rotor 205 isheterogeneous in voltage, or a border zone of healthy and scar tissue.In fact, the substrate based rotor 205 appears to migrate along avoltage transition zone over multiple phases of atrial fibrillation muchlike a tornado would form and move along a high pressure and lowpressure weather border zone in nature.

FIG. 2D depicts the left atrium of FIGS. 2A-2C with a complexfractionated atrial electrogram map (CFAE) 275. The CFAE map 275highlights areas having noisy fractionation of electrograms (EGMs)versus areas with less fractionation of EGMs. While difficult to see inthe grey-scale depiction of FIG. 2D, the area around non-substrate basedrotor 215 has noisy fractionation of EGMs, indicating a non-substratebased rotor. The area around substrate based rotor 205 has lessfractionation of EGMs, indicating a substrate based rotor. Fractionationcan be associated with electrical wavefronts colliding rather thantissue causing or driving an arrhythmia.

As another example of an electro-anatomical model, FIG. 3A is anelectro-anatomical model 300 of a left atrium showing cardiac conductionpatterns. Electro-anatomical model 300 depicts two non-substrate basedrotors 305 and one substrate based rotor 310 characterized by swirlingconduction vectors 315.

As another example of a voltage map, FIG. 3B depicts voltage map 325.Voltage map 325 depicts the left atrium of FIG. 3A, highlighting bordersof healthy tissue meeting scar or dead tissue resulting in high voltagetransition deltas. As described in further detail herein, the presenceof rotor 310 in a voltage transition region 330 is indicative of rotor310 being a substrate based rotor. Treatment (i.e., ablation) of thenon-substrate based rotors 325 for this patient did not improve cardiacrhythm. Treatment of the substrate-based rotor 310 resulted insignificant improvements in heart rhythm for this patient.

Similarly, FIG. 9A depicts an electro-anatomical model 900 showing asubstrate based rotor 905 characterized by swirling conduction pattern910 within the left atrial appendage. FIG. 9B depicts a voltage map thatfurther confirms rotor 905 is a substrate based rotor as it is in anarea of high voltage heterogeneity. FIG. 9C is an EKG readout of theheartbeat of the patient belonging to the heart in FIGS. 9A and 9B. Whenthe rotor 905 was ablated, atrial fibrillation as seen in the EKG at 920converted into normal sinus rhythm at 925. Ablation at other locations915 (FIG. 9A) produced no such rhythm change in the patient's heartbeat.

As mentioned above, at 160, the rotors classified as substrate rotorscan be treated (e.g., ablated or burned) to improve cardiac activity inthe patient. Treatment can be performed by known tools and instrumentswithin the field. For example, an ablation catheter can be used to burnthe heart tissue near the substrate based rotor. The ablation cathetercan be tracked and monitored using a tracking system such as, forexample, the tracking system disclosed in U.S. patent application Ser.No. 13/747,266 as described above. Treatment of substrate rotors, at160, is strongly correlated with improved cardiac rhythms. Non-substraterotors may not be treated, at 160. Treatment of non-substrate rotors isnot correlated with, or is only weakly correlated with improved cardiacrhythms. In an embodiment where only substrate rotors are treated,treatment time can be reduced and/or more cardiac tissue can bepreserved as compared to an embodiment where substrate and non-substraterotors are treated.

Turning now to FIG. 4, it is a decision tree 400 for classifying rotors.In some embodiments, this decision tree can be used at 150 (FIG. 1) forclassifying the rotors. In some embodiments, rotors can be classifiedbased on three criteria, stability, voltage change, and complexfractionation level. In some embodiments, rotors can also be classifiedbased on rotational patterns of wavefronts and/or any other suitablefeature.

At decision branch 410, a rotor can be evaluated for stability based,for example, on determining how many phases out of a total number ofphases the rotor appears in. A phase can be, for example, a distinctpattern identified by a far-field electrogram measurement instrument. Arotor that presents in thirty percent (30%) or more of the total phasescan be considered to be stable.

In some embodiments, a far-field instrument can be in a stable location(e.g., the coronary sinus) and the electrogram information from thefar-field instrument can be monitored. A near-field instrument can belocated within a chamber of the patient's heart. A phase can beidentified by a unique pattern detected in the far-field electrograminformation. When that phase is identified, electrogram information usedto build an electro-anatomical model of the patent's heart can becaptured from the near-field instrument. The near-field instrument canthen be moved to another location within the heart chamber. Once theunique pattern is detected in the far-field electrogram information, thenear-field electrogram information can be captured for that location inthe patient's heart. The process can be repeated until multiple pointsof data are collected for areas within the chamber of the patient'sheart such that a complete electro-anatomical model (e.g., FIG. 2A) ofthe patient's heart can be constructed for that unique phase.Additionally, a second unique pattern can be identified in the far-fieldelectrogram information, which can represent a second phase. The processdescribed can be completed to capture information from the near-fieldinstrument to construct an electro-anatomical model (e.g., FIG. 2B) ofthe patent's heart for the second unique phase. Once multipleelectro-anatomical models of the patent's heart are constructed formultiple phases, stable rotors can appear in multiple of the models(e.g., 30% or more of the models).

After evaluating for stability at 410, rotors can be evaluated based onwhether they are in a voltage transition zone. A voltage transition zoneis a region of heart tissue characterized by a relatively large changein electrical potential (high ΔV) over a relatively short distance. Asmeasured in atrial fibrillation, a change of greater than 0.23 mV can bedetermined to be a high voltage transition. A voltage transition zonecan be associated with healthy tissue meeting dead or scarred tissue.For example, rotor 205 (FIG. 2A) can be migrating along a voltagetransition zone, as shown in FIG. 2C, while rotor 215 is not disposed ina voltage transition zone.

Rotors determined to be stable, at 410, are evaluated for voltagetransition, at 415. If a rotor is stable and in a voltage transitionzone, such as rotor 310, it can be classified as a substrate rotor.Rotors that are determined to be unstable at 410 are evaluated forvoltage transition at 420. If a rotor is unstable and not in a voltagetransition zone, such as rotor 215, the rotor can be classified as anon-substrate rotor.

If a rotor is stable and not in a voltage transition zone or unstableand in a voltage transition zone, complex fractionation level can beevaluated at 425 and 430 respectively. Either type of rotor evaluated at425 or 430 with a low complex fractionation can be classified as asubstrate rotor. Conversely, either type of rotor evaluated at 425 or430 with a high complex fractionation can be classified as anon-substrate rotor.

FIGS. 5 A-D describe an example of an embodiment of the presentinvention. FIG. 5A is an illustration of a human heart having afar-field measurement instrument 520 including multiple electrodes,which can be placed in a stable location, such as, for example, thecoronary sinus. FIG. 5B is an illustration of a different view of thehuman heart having a roving near-field measurement instrument 530including multiple electrodes, which can be placed at various locationswithin the heart to gather local electrogram data. FIG. 5D is anillustration of the heart and the various locations 540 within the heartfrom which electrogram data can be gathered. Local conduction vectordata can be calculated and associated with the position of thenear-field measurement instrument. FIG. 5C depicts patterns 510 that canbe identified on the far-field instrument electrode data 515simultaneously during near-field signal measurement. FIG. 5D furtherillustrates that multiple locations and associated near-field data 545that occurred when the same pattern 510 (FIG. 5C) was occurring on thefar-field electrode data can be assembled into a consistent phase map550, presuming the heart is beating in a certain condition during thisphase.

FIGS. 6A-6C depict the intracardiac electrical signals or electrograms610 acquired by electrodes on cardiac instruments, such as, for example,the instrument depicted in FIG. 10. These signals display thedepolarization of the cells in contact with the measurement electrode asthe tissue contracts in the heart.

FIG. 6B illustrates how certain morphologies of the electrical signalssuch as the greatest change in voltage divided by change in time 620(ΔV/ΔT) can be used to identify a trigger point for timing andidentification of when the heart cells are depolarizing or contracting.

FIG. 6C illustrates how to use known X-Y-Z electrode positions, asmeasured by a tracking system, and the timing of when the cells incontact with each electrode are depolarizing or triggering to calculatea direction and magnitude of the a cardiac conduction wavefront in theregion of the electrodes at each electrode X-Y-Z location. Eachcalculated direction and magnitude at each electrode is considered ameasured conduction vector.

FIG. 7 illustrates an example of how conduction vectors 740 can bestored in a look-up table in some embodiments. Memory 750 can be RAM,ROM, a hard drive, a storage drive, and or any other suitable memorydevice. The position and electrogram data (e.g., data captured at 120 ofFIG. 1) can be stored in memory 750. The data can include informationfrom different positions in the heart and associated with differentphases 720 or patterns occurring on the far-field instrument's data. Thedata can be, for example, 3D vector information for each position of theinstrument and for each phase. This information can be used, asdescribed in further detail in FIGS. 1 and 11 to construct conductionvector maps and electro-anatomical models.

FIGS. 8A-8C depict how measured conduction vectors of a particular phasecan be interpolated over a spatial region in order to create a completeconduction vector map for the entire region. First, conduction vectorscan be calculated for each electrode of a roving instrument (e.g., theinstrument of FIG. 10) electrode position 840 during a particular phase.Next, the distance from non-measured points to actual electrodepositions can be calculated using the formulas shown at 850. Further,the direction value and magnitude value of a conduction vector at agiven non-measured point can be calculated using the formulas shown at860 from all surrounding actual measured conduction vectors. Theresulting information can be constructed into a conduction vector map870.

Multiple conduction vector maps can be constructed over a period oftime. The conduction vector maps can be 3D maps, which can further besequenced by the control unit into a 4D map to show the various statesof electrical conductivity of the heart over time.

The 3D and 4D maps created can be superimposed on a model of thepatent's heart, such as the model constructed as described in FIG. 1 at110. The 3D and 4D maps can be displayed in 3D for visualization withbi-color glasses, polarized glasses, shuttered glasses, or any othersuitable viewing device that can be used to give true 3D perspective tothe viewer.

FIG. 10 is a schematic illustration of the distal portion of an antennareference instrument 1000, in accordance with an illustrative embodimentof the invention. Antenna reference instrument 1000 can be any medicalinstrument that can be adapted to be inserted into the thorax of asubject and includes multiple electrodes 1010. In some embodiments,antenna reference instrument can include distal cap electrode 1030. Forexample, as shown in FIG. 10, antenna reference instrument 1000 caninclude multiple electrodes 1010, 1030 for sensing current, voltage, orimpedance, as well as electromagnetic sensor 1020 for sensing anelectromagnetic field. Antenna reference instrument 1000 can include acatheter system, a pacemaker lead system, an implantable cardioverterdefibrillator lead system, or any other suitable medical device,depending on the particular embodiment. Antenna reference instrument1000 can be, for example, the antenna reference instrument disclosed inU.S. patent application Ser. No. 13/747,266 as described above.

Antenna reference instrument 1000 can be the near-field instrumentand/or the far-field instrument described herein with respect to thedescriptions of other figures.

FIG. 11 describes a method for capturing the electrogram informationfrom the near-field and far-field instruments. This can be used, forexample, as the method described in FIG. 1 at 120.

At 1105, a control unit can receive the position coordinates from anear-field instrument. The position coordinates can be in X-Y-Z spaceand can be identified using the multiple electrodes on the near-fieldinstrument and/or an electromagnetic sensor in the near-fieldinstrument. As described above with respect to FIG. 1, the positioncoordinates can be obtained with a tracking system designed to locate amedical instrument within the heart of a patient during a cardiovascularprocedure.

At 1110, the control unit can receive electrogram information from thefar-field instrument. In some embodiments, the electrogram informationcan continue to stream to the control unit without interruption. Inother embodiments, the electrogram information can be sent for shorterperiods of time. The control unit can monitor the electrograminformation to identify a unique pattern in the electrogram data at1115. The duration that the unique pattern can be detected in theelectrogram information from the far-field instrument can be considereda phase of the monitored heart. In some embodiments, multiple patternscan be identified in the far-field electrogram data, which can be usedto identify multiple phases of the monitored heart.

Once a unique pattern is identified at 1115, electrogram information canbe received at the control unit from the near-field instrument at 1120.In this way, the electrogram information from the near-field instrumentcorresponds to the identified pattern or phase of the monitored heart.

At 1125, the control unit can store and associate the unique patterninformation, the position coordinates of the near-field instrument, andthe electrogram data from the near-field instrument in storage, such asthe storage depicted in FIG. 7.

At 1130, the near-field instrument can be moved within the patient'sheart chamber, and the control unit can receive the new positioncoordinates of the near-field instrument. At 1135 the control unit canreceive electrogram information from the far-field instrument. In someembodiments, the control unit can receive the electrogram informationfrom the far-field instrument continuously and can continue to receiveit between 1110 and 1135. While the near-field instrument remains at thenew location within the patient's heart chamber, the control unit canmonitor the far-field electrogram information to detect the uniquepattern associated with the identified phase from 1115. When the patternis detected, at 1140, the control unit can receive electrograminformation from the near-field instrument at the second location. Inthis way, the control unit can have information from two differentlocations within the patient's heart chamber and the information caneach be associated with the respective unique pattern identified in thefar-field electrogram information.

At 1145, the control unit can store and associate the positioncoordinates and the electrogram data from the near-field instrument andassociate it with the unique pattern information. In some embodiments,the process of obtaining near-field electrogram information associatedwith different positions within the patient's heart chamber and theunique pattern can be repeated as many or as few times as desired toobtain the information needed to construct a conduction vector map, orany other suitable map or model, of the patient's heart.

At 1150, the control unit can calculate a direction value and amagnitude value of the conduction wavefront at each electrode of thenear-field instrument as described in more detail with respect to FIGS.5 and 8. At 1155, the control unit can generate an interpolateddirection value and magnitude value of the conduction wavefront betweeneach of the values calculated at 1150. The interpolation is described inmore detail with respect to FIG. 8.

At 1160, the control unit can use the calculated and interpolated valuesfrom 1150 and 1155 to generate a conduction vector map as described inmore detail with respect to FIG. 8.

While various embodiments have been described above, it should beunderstood that they have been presented by way of example only, and notlimitation. Where methods and/or flowcharts described above indicatecertain events and/or flow patterns occurring in a certain order, theordering of certain events and/or flow patterns may be modified. Whilethe embodiments have been particularly shown and described, it will beunderstood that various changes in form and details may be made.

For instance, in some embodiments multiple roving instruments may beused. In those embodiments, multiple measurement steps can be done todetermine each roving instrument's location. Those measurement steps canbe done in parallel, but they need not be done in parallel, depending onthe embodiment.

While various embodiments have been described above, it should beunderstood that they have been presented by way of example only, and notlimitation. Furthermore, although various embodiments have beendescribed as having particular features and/or combinations ofcomponents, other embodiments are possible having a combination of anyfeatures and/or components from any of embodiments where appropriate aswell as additional features and/or components.

Where methods described above indicate certain events occurring incertain order, the ordering of certain events may be modified.Additionally, certain of the events may be performed repeatedly,concurrently in a parallel process when possible, as well as performedsequentially as described above. Where methods are described above, itshould be understood that the methods can be computer implementedmethods having instructions stored on a non-transitory medium (e.g., amemory) and configured to be executed by a processor. For example, someor all of the steps shown and described with reference to FIGS. 1 and/or4 can be implemented on a computer. For example, a compute device havinga processor and a memory can include modules (e.g., hardware and/orsoftware (executing or configured to execute on a processor)) operableto receive data, define models, identify and/or classify rotors, and/orso forth.

Some embodiments described herein relate to computer-readable medium. Acomputer-readable medium (or processor-readable medium) isnon-transitory in the sense that it does not include transitorypropagating signals per se (e.g., a propagating electromagnetic wavecarrying information on a transmission medium such as space or a cable).The media and computer code (also can be referred to as code) may bethose designed and constructed for the specific purpose or purposes.Examples of non-transitory computer-readable media include, but are notlimited to: magnetic storage media such as hard disks, floppy disks, andmagnetic tape; optical storage media such as Compact Disc/Digital VideoDiscs (CD/DVDs), Compact Disc-Read Only Memories (CD-ROMs), andholographic devices; magneto-optical storage media such as opticaldisks; carrier wave signal processing modules; and hardware devices thatare specially configured to store and execute program code, such asASICs, PLDs, ROM and RAM devices. Other embodiments described hereinrelate to a computer program product, which can include, for example,the instructions and/or computer code discussed herein. Examples ofcomputer code include, but are not limited to, micro-code ormicro-instructions, machine instructions, such as produced by acompiler, code used to produce a web service, and files containinghigher-level instructions that are executed by a computer using aninterpreter. For example, embodiments may be implemented using Java,C++, or other programming languages (e.g., object-oriented programminglanguages) and development tools. Additional examples of computer codeinclude, but are not limited to, control signals, encrypted code, andcompressed code.

What is claimed is:
 1. A method, comprising: placing a far-fieldinstrument on or in a patient such that the far-field instrument ispositioned to receive far-field electrogram information from a stableposition relative to a heart of a patient; placing a near-fieldinstrument at a first position within a chamber of the heart; capturing,at a first time, near-field electrogram information from the near-fieldinstrument while the near-field instrument is at the first position;associating the near-field electrogram information captured at the firsttime at the first position with far-field electrogram informationreceived by the far-field instrument at the first time; moving thenear-field instrument to a second position within the chamber of theheart; identifying, at a second time, a far-field electrogram patternreceived from the far-field instrument that corresponds to the far-fieldelectrogram information received at the first time; capturing, at thesecond time, near-field electrogram information from the near-fieldinstrument while the near-field instrument is at the second position;and assembling an electro-anatomical model of a phase of the heart thatincludes the first position and the second position based on (i) thenear-field electrogram information captured at the first time and (ii)the near-field electrogram information captured at the second time. 2.The method of claim 1, wherein the far-field instrument is a coronarysinus catheter.
 3. The method of claim 1, wherein: the far-fieldinstrument includes a plurality of electrodes; and placing the far-fieldinstrument includes affixing the plurality of electrodes on an externalsurface of the patient's body.
 4. The method of claim 1, furthercomprising identifying a swirling conduction pattern in theelectro-anatomical model, the swirling conduction pattern spanning thefirst position and the second position.
 5. The method of claim 1,wherein the phase is a first phase and the far-field electrogram patternis a first far-field electrogram pattern, the method further comprising:capturing, at a third time, near-field electrogram information from thenear-field instrument while the near-field instrument is at the firstposition, the third time being between the first time and the secondtime; associating the near field electrogram information captured at thethird time at the first position with far-field information received bythe far-field instrument at the third time; after moving the near-fieldinstrument to the second position, identifying a second far-fieldelectrogram pattern received from the far-field instrument at a fourthtime that corresponds to the far-field electrogram information receivedat the third time; capturing, at the fourth time, near-field electrograminformation from the near-field instrument while the near-fieldinstrument is at the second position; and assembling anelectro-anatomical model of a second phase of the heart that includesthe first position and the second position based on (i) the near-fieldelectrogram information captured at the third time and (ii) thenear-field information captured at the fourth time.
 6. The method ofclaim 5, further comprising: receiving positional information of thenear-field instrument at the first time, the second time, the thirdtime, and the fourth time; and assembling the electro-anatomical modelof the first phase of the heart and the electro-anatomical model of thesecond phase of the heart into a four-dimensional electro-anatomicalmodel of the heart that includes at least the first position, the secondposition, the first time, and the third time.
 7. The method of claim 5,further comprising: identifying a swirling conduction pattern in theelectro-anatomical model of the first phase of the heart, the swirlingconduction pattern spanning the first position and the second position;identifying the swirling conduction pattern in the electro-anatomicalmodel of the second phase of the heart; and identifying the swirlingconduction pattern as a stable rotor based on the swirling conductionpattern being present in both the electro-anatomical model of the firstphase of the heart and the electro-anatomical model of the second phaseof the heart.
 8. The method of claim 1, further comprising: moving thenear-field instrument from the second position to a third position afterthe second time; identifying, at a third time, the far-field electrogrampattern received from the far-field instrument that corresponds to thefar-field electrogram information received at the first time; andcapturing, at the third time, near-field electrogram information fromthe near-field instrument while the near field instrument is at thethird position, assembling an electro-anatomical model of the phase ofthe heart includes the first position, the second position, and thethird position based on (i) the near-field electrogram informationcaptured at the first time, (ii) the near-field electrogram informationcaptured at the second time, and (iii) the near-field electrograminformation captured at the third time.
 9. The method of claim 1,wherein the near-field instrument is a multi-electrode roving catheter.10. The method of claim 1, wherein a compute device is configured tocapture the near-field electrogram information at the second time whenthe compute device receives, from the far-field instrument, thefar-field electrogram information at the second time that corresponds tothe far-field electrogram information received at the first time. 11.The method of claim 1, wherein the electro-anatomical model of the phaseof the heart includes a vector field indicating conduction patterns. 12.The method of claim 1, further comprising: identifying a swirlingconduction pattern in the electro-anatomical model; and ablatingcoronary tissue associated with the swirling conduction pattern.
 13. Asystem comprising: a far-field instrument configured to be placed in astable position relative to a heart of a patient, the far-fieldinstrument configured to measure far-field electrogram information; acompute device communicatively coupled to the far-field instrument andconfigured to identify a plurality of unique patterns in the far-fieldelectrogram information, each unique pattern from the plurality ofunique patterns associated with a phase of the heart; and a near-fieldinstrument communicatively coupled to the compute device and configuredto be disposed in a chamber of the heart, the near-field instrumentconfigured to move from a first position within the chamber of the heartto a second position within the chamber of the heart, the compute deviceconfigured to: associate near-field electrogram information receivedfrom the near-field instrument when the near-field instrument is at thefirst position with a first phase from the plurality of phases;associate near-field electrogram information received from thenear-field instrument when the near-field instrument is at the secondposition with the first phase; and assemble an electro-anatomical modelof the first phase of the heart based on (i) the near-field electrograminformation received when the near-field instrument is at the firstposition and (ii) the near-field electrogram information received whenthe near-field instrument is at the second position.
 14. The system ofclaim 13, wherein: the near-field electrogram information received fromthe near-field instrument when the near-field instrument is at the firstposition is received at first time; and the near-field electrograminformation received from the near-field instrument when the near-fieldinstrument is at the second position is received at a second time. 15.The system of claim 13, wherein: the near-field electrogram informationreceived from the near-field instrument when the near-field instrumentis at the first position is received at first time; the near-fieldelectrogram information received from the near-field instrument when thenear-field instrument is at the second position is received at a secondtime; and the compute device is further configured to: associatenear-field electrogram information received from the near-fieldinstrument when the near-field instrument is at the first position at athird time with a second phase from the plurality of phases; associatenear-field electrogram information received from the near-fieldinstrument when the near-field instrument is at the second position at afourth time with the second phase from the plurality of phases; andassemble an electro-anatomical model of the second phase of the heartbased on (i) the near-field electrogram information received from thenear-field instrument at the third time and (ii) the near-fieldelectrogram information received from the near-field instrument for atthe fourth time.
 16. The system of claim 15, wherein the compute deviceis further configured to identify stable rotors based on a swirlingconduction pattern being present in the first phase and the secondphase.
 17. The system of claim 13, wherein the first phase is associatedwith a phase of atrial fibrillation of the heart.
 18. The system ofclaim 13, wherein the compute device is further configured to identifyrotors based on the electro-anatomical model.
 19. The system of claim13, wherein: the near-field electrogram information received from thenear-field instrument when the near-field instrument is at the firstposition is received at first time; the near-field electrograminformation received from the near-field instrument when the near-fieldinstrument is at the second position is received at a second time; andthe compute device is configured to: receive positional informationassociated with the near-field instrument at the first time; and receivepositional information associated with the near-field instrument at thesecond time, the electro-anatomical model of the first phase of theheart including the first position and the second position and assembledbased on the positional information received at the first time and thepositional information received at the second time.